Towards automatic computer‐aided knee surgery by innovative methods for processing the femur surface model

Abstract

The proposed method proved that: (a) the AFA can be robustly computed by a geometrical analysis of the posterior profiles of the two condyles and can be considered a useful alternative to the TA; (b) higher surface resolutions leads to higher repeatability of all computed quantities; (c) the TA is less repeatable than the other axes.

Determination of the Whiteside line on femur surface models by fitting high-order polynomial functions to cross-section profiles of the intercondylar fossa

“…Taking advantage of improvements in imaging technologies and image processing techniques, easier manual analyses of the 3D geometry of the distal femur have recently been undertaken [41,[45][46][47][48]. Nonetheless, manual detection is still subjective and inevitably entails low (4.5 mm) reproducibility of the point landmarks, easily leading to angular skew of approximately 3-4 [10,14].…”

“…These methods allow determination of the optimal implant size and positioning according to the computed clinical landmarks, visualization of the virtual bone resections, and simulation of the entire intervention prior to surgery [6][7][8][9][10][11][12][13][14][15][16]. As an added value, they provide functionalities, based on bone surface analysis, for designing and modeling personalized resection guides that can be used during the TKR procedure, substituting for the traditional jigs and avoiding the need for any other alignment instrument or navigation support [17][18][19].…”

“…In earlier publications [13,14], we proposed a computational framework to process the 3D shape model of the femur and extract the shaft, distal and proximal parts. A method based on geometric-based analysis allowed the extraction of the femoral head and neck from the proximal femur, and a spherefitting algorithm was used to compute the center and radius of the femoral head [13].…”

“…A method based on geometric-based analysis allowed the extraction of the femoral head and neck from the proximal femur, and a spherefitting algorithm was used to compute the center and radius of the femoral head [13]. The automatic processing of the distal femur surface allowed 3D segmentation of the condyles and intercondylar fossa [14]. Building on these earlier results, we here propose a method that uses a cutting plane, parallel to the frontal plane, to obtain the 2D profiles of the intercondylar fossa.…”

Mean-shifted surface curvature algorithm for automatic bone shape segmentation in orthopedic surgery planning: a sensitivity analysis

“…Statistical models of bone structures have been investigated extensively with the aim of enhancing automation in CT and MR image segmentation [6][7][8][9][10][11][12] and reconstructing patientspecific shape models from a small number of X-ray images or even from a single image [13][14][15]. Innovative methods for bone shape analysis have been applied to 3D mesh segmentation and clinical feature detection [16][17][18][19][20][21]. In this domain, automatic shape analysis is strongly advocated because it offers the opportunity to detect morphological and clinical landmarks (MCL) with superior repeatability in comparison to human operators.…”